Senior Data & AI Governance Analyst

New

Based in BrazilFull-TimeSenior

Salary not disclosed

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Job Details

Bring proven experience in data and AI governance, including policies, processes, standards, metadata management, and data cataloging.
Have experience with Databricks and Unity Catalog or equivalent platforms, including metadata, classification, access controls, lineage, and auditing.
Know relational and multidimensional data modeling.
Understand Medallion Architecture and its Bronze, Silver, and Gold layers.
Have experience with Data Lake and Data Lakehouse environments from ingestion through data consumption.
Have experience designing and implementing data access management models, including RBAC and least-privilege principles.
Know Information Security best practices and LGPD requirements throughout the data lifecycle.
Have strong SQL skills for diagnostics, access audits, and governance-indicator automation.
Have experience defining KPIs and building dashboards using Power BI, Lakeview, or Metabase.
Have applied knowledge of DAMA-DMBOK or similar data management frameworks.
Understand Data Mesh, DataOps/MLOps, and Hub-and-Spoke operating models.
Have practical experience using generative AI and AI agents to automate tasks and improve workflows.
Hold a bachelor's degree in Technology or a related field.

Execute end-to-end data and AI governance initiatives, defining policies, responsibilities, standards, and best practices across the data lifecycle.
Establish governance frameworks, including Data Owner and Data Steward roles.
Guide junior and mid-level analysts and Analytics Engineers on governance implementation and consistent practices.
Lead the corporate data catalog using Unity Catalog and OpenMetadata, overseeing metadata, classification, lineage, and business glossaries.
Design and implement RBAC models and access lifecycle processes with Data Engineering and Identity and Access Management teams.
Establish data quality frameworks, including SLAs, observability practices, and incident response for critical datasets.
Implement cost governance for the analytical sandbox, including showback models and usage policies.
Lead regulatory and privacy governance initiatives related to BACEN requirements and LGPD, and support audits with data dictionaries, lineage documentation, and quality controls.
Define governance standards for predictive and generative AI, including inventories, model cards, monitoring, and usage guidelines.
Develop governance dashboards and indicators, and promote data literacy and secure self-service BI practices.

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